Example usage for org.apache.commons.math3.linear RealMatrix setEntry

Introduction

In this page you can find the example usage for org.apache.commons.math3.linear RealMatrix setEntry.

Prototype

void setEntry(int row, int column, double value) throws OutOfRangeException;

Source Link

Document

Set the entry in the specified row and column.

Usage

From source file:com.itemanalysis.psychometrics.factoranalysis.MatrixUtils.java

/**
 * Creates a vector (1 X size matrix) with all elements set to value.
 *
 * @param size/*  ww w .  j  a  v a 2s.  c  om*/
 * @param value
 * @return
 */
public static RealMatrix getVector(int size, double value) {
    RealMatrix vec = new Array2DRowRealMatrix(1, size);
    for (int i = 0; i < size; i++) {
        vec.setEntry(0, i, value);
    }
    return vec;
}

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From source file:com.cloudera.oryx.common.math.SolverLoadIT.java

private static RealMatrix randomSymmetricMatrix(int dimension) {
    RandomGenerator random = RandomManager.getRandom();
    RealMatrix symmetric = new Array2DRowRealMatrix(dimension, dimension);
    for (int j = 0; j < dimension; j++) {
        // Diagonal
        symmetric.setEntry(j, j, random.nextDouble());
        for (int k = j + 1; k < dimension; k++) {
            // Off-diagonal
            double d = random.nextDouble();
            symmetric.setEntry(j, k, d);
            symmetric.setEntry(k, j, d);
        }//from  ww  w  .ja  va 2s. c  o  m
    }
    return symmetric;
}

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From source file:com.google.location.lbs.gnss.gps.pseudorange.Ecef2EnuConverter.java

/**
 * Computes a rotation matrix for converting a vector in Earth-Centered Earth-Fixed (ECEF)
 * Cartesian system into a vector in local east-north-up (ENU) Cartesian system with respect to
 * a reference location. The matrix has the following content:
 *
 * - sinLng                     cosLng            0
 * - sinLat * cosLng      - sinLat * sinLng      cosLat
 *   cosLat * cosLng        cosLat * sinLng      sinLat
 *
 * <p> Reference: Pratap Misra and Per Enge
 * "Global Positioning System: Signals, Measurements, and Performance" Page 137.
 *
 * @param refLat Latitude of reference location
 * @param refLng Longitude of reference location
 * @return the Ecef to Enu rotation matrix
 *///from  w w  w.  ja  v a 2  s .c  o m
public static RealMatrix getRotationMatrix(double refLat, double refLng) {
    RealMatrix rotationMatrix = new Array2DRowRealMatrix(3, 3);

    // Fill in the rotation Matrix
    rotationMatrix.setEntry(0, 0, -1 * Math.sin(refLng));
    rotationMatrix.setEntry(1, 0, -1 * Math.cos(refLng) * Math.sin(refLat));
    rotationMatrix.setEntry(2, 0, Math.cos(refLng) * Math.cos(refLat));
    rotationMatrix.setEntry(0, 1, Math.cos(refLng));
    rotationMatrix.setEntry(1, 1, -1 * Math.sin(refLat) * Math.sin(refLng));
    rotationMatrix.setEntry(2, 1, Math.cos(refLat) * Math.sin(refLng));
    rotationMatrix.setEntry(0, 2, 0);
    rotationMatrix.setEntry(1, 2, Math.cos(refLat));
    rotationMatrix.setEntry(2, 2, Math.sin(refLat));
    return rotationMatrix;
}

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From source file:com.itemanalysis.psychometrics.factoranalysis.MatrixUtils.java

/**
 * Elementwise multiplication of elements in two arrays. This is equivalent to
 * using A*B in R when both A and B are matrices.
 *
 * @param A a matrix/*from ww w.j ava  2  s .c  o  m*/
 * @param B a matrix of the same dimension as A
 * @return a matrix with elements that are the produce of elements in A and B.
 * @throws org.apache.commons.math3.exception.DimensionMismatchException
 */
public static RealMatrix multiplyElements(RealMatrix A, RealMatrix B) throws DimensionMismatchException {
    int nrow = A.getRowDimension();
    int ncol = A.getColumnDimension();
    if (nrow != B.getRowDimension()) {
        throw new DimensionMismatchException(nrow, B.getRowDimension());
    }
    if (ncol != B.getColumnDimension()) {
        throw new DimensionMismatchException(ncol, B.getColumnDimension());
    }

    RealMatrix M = new Array2DRowRealMatrix(nrow, ncol);
    for (int i = 0; i < nrow; i++) {
        for (int j = 0; j < ncol; j++) {
            M.setEntry(i, j, A.getEntry(i, j) * B.getEntry(i, j));
        }
    }
    return M;
}

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From source file:com.cloudera.oryx.common.math.MatrixUtilsTest.java

public static RealMatrix multiplyXYT(LongObjectMap<float[]> X, LongObjectMap<float[]> Y) {
    int Ysize = Y.size();
    int Xsize = X.size();
    RealMatrix result = new Array2DRowRealMatrix(Xsize, Ysize);
    for (int row = 0; row < Xsize; row++) {
        for (int col = 0; col < Ysize; col++) {
            result.setEntry(row, col, SimpleVectorMath.dot(X.get(row), Y.get(col)));
        }//from   w ww. j  a v a  2  s .c om
    }
    return result;
}

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From source file:edu.washington.gs.skyline.model.quantification.WeightedRegression.java

public static double[] weighted(double[][] x, double[] y, double[] weights, boolean intercept) {
    RealMatrix predictor;
    if (intercept) {
        int nRows = x.length;
        int nCols = x[0].length + 1;
        predictor = MatrixUtils.createRealMatrix(nRows, nCols);
        for (int iRow = 0; iRow < nRows; iRow++) {
            predictor.setEntry(iRow, 0, 1.0);
            for (int iCol = 1; iCol < nCols; iCol++) {
                predictor.setEntry(iRow, iCol, x[iRow][iCol - 1]);
            }/*from   w  w w. ja  v a  2  s  .  c om*/
        }
    } else {
        predictor = MatrixUtils.createRealMatrix(x);
    }
    RealVector responseVector = MatrixUtils.createRealVector(y);
    RealMatrix weightsMatrix = MatrixUtils.createRealDiagonalMatrix(weights);
    RealMatrix predictorTransposed = predictor.transpose();
    RealMatrix predictorTransposedTimesWeights = predictorTransposed
            .multiply(weightsMatrix.multiply(predictor));
    CholeskyDecomposition choleskyDecomposition = new CholeskyDecomposition(predictorTransposedTimesWeights);
    RealVector vectorToSolve = predictorTransposed.operate(weightsMatrix.operate(responseVector));
    RealVector result = choleskyDecomposition.getSolver().solve(vectorToSolve);
    return result.toArray();
}

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From source file:net.sf.dsp4j.octave_3_2_4.m.polynomial.Roots.java

public static Complex[] roots(RealVector v) {

    if (v.isInfinite() || v.isNaN()) {
        throw new RuntimeException("roots: inputs must not contain Inf or NaN");
    }/*from   ww  w .ja  v a 2 s  . co  m*/

    int n = v.getDimension();

    // ## If v = [ 0 ... 0 v(k+1) ... v(k+l) 0 ... 0 ], we can remove the
    // ## leading k zeros and n - k - l roots of the polynomial are zero.

    int[] f = new int[v.getDimension()];
    if (v.getDimension() > 0) {
        int fI = 0;
        double max = v.getMaxValue();
        double min = FastMath.abs(v.getMinValue());
        if (min > max) {
            max = min;
        }
        RealVector v1 = v.mapDivide(max);
        f = OctaveBuildIn.find(v1);
    }

    Complex[] r = new Complex[0];
    if (f.length > 0 && n > 1) {
        v = v.getSubVector(f[0], f[f.length - 1] - f[0] + 1);
        if (v.getDimension() > 1) {
            double[] ones = new double[v.getDimension() - 2];
            Arrays.fill(ones, 1);
            RealMatrix A = OctaveBuildIn.diag(ones, -1);
            for (int i = 0; i < A.getRowDimension(); i++) {
                A.setEntry(i, 0, -v.getEntry(i + 1) / v.getEntry(0));
            }
            try {
                r = Eig.eig(A);
            } catch (Exception e) {
                throw new RuntimeException(e);
            }
            if (f[f.length - 1] < n) {
                int diffLength = n - 1 - f[f.length - 1];
                if (diffLength > 0) {
                    int rl = r.length;
                    r = Arrays.copyOf(r, r.length + diffLength);
                    Arrays.fill(r, rl, r.length, Complex.ZERO);
                }
            }
        } else {
            r = new Complex[n - f[f.length - 1]];
            Arrays.fill(r, Complex.ZERO);
        }
    } else {
        r = new Complex[0];
    }
    return r;

}

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From source file:edu.washington.gs.skyline.model.quantification.DesignMatrix.java

private static RealMatrix matrixFromColumnVectors(double[][] columnVectors) {
    RealMatrix realMatrix = MatrixUtils.createRealMatrix(columnVectors[0].length, columnVectors.length);
    for (int iRow = 0; iRow < realMatrix.getRowDimension(); iRow++) {
        for (int iCol = 0; iCol < realMatrix.getColumnDimension(); iCol++) {
            realMatrix.setEntry(iRow, iCol, columnVectors[iCol][iRow]);
        }//w ww  . ja va 2  s.  com
    }
    return realMatrix;
}

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From source file:com.simiacryptus.mindseye.test.PCAUtil.java

/**
 * Forked from Apache Commons Math//w w w  . j  a  va2s .  c  o  m
 *
 * @param stream the stream
 * @return covariance covariance
 */
@Nonnull
public static RealMatrix getCovariance(@Nonnull final Supplier<Stream<double[]>> stream) {
    final int dimension = stream.get().findAny().get().length;
    final List<DoubleStatistics> statList = IntStream.range(0, dimension * dimension)
            .mapToObj(i -> new DoubleStatistics()).collect(Collectors.toList());
    stream.get().forEach(array -> {
        for (int i = 0; i < dimension; i++) {
            for (int j = 0; j <= i; j++) {
                statList.get(i * dimension + j).accept(array[i] * array[j]);
            }
        }
        RecycleBin.DOUBLES.recycle(array, array.length);
    });
    @Nonnull
    final RealMatrix covariance = new BlockRealMatrix(dimension, dimension);
    for (int i = 0; i < dimension; i++) {
        for (int j = 0; j <= i; j++) {
            final double v = statList.get(i + dimension * j).getAverage();
            covariance.setEntry(i, j, v);
            covariance.setEntry(j, i, v);
        }
    }
    return covariance;
}

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From source file:edu.mit.genecircuits.GcUtils.java

/** Convert dense Colt to Apache Commons matrix */
static public RealMatrix colt2apache(DoubleMatrix2D colt) {

    RealMatrix apache = MatrixUtils.createRealMatrix(colt.rows(), colt.columns());
    for (int i = 0; i < colt.rows(); i++)
        for (int j = 0; j < colt.columns(); j++)
            apache.setEntry(i, j, colt.get(i, j));

    return apache;
}

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